This disclosure relates generally to the field of digital image capture and processing, and more particularly to the field of vision based 3D reconstruction and object tracking.
Three dimensional reconstruction methods involve determining various intrinsic and extrinsic parameters of a camera in order to determine a depth of a given 2D image. Depending on the application, the accuracy and precision of the estimation may need to be somewhat strict. For example certain applications require extremely accurate estimation, and errors in the estimation may deem the applications unusable. Some examples of applications that rely on strict camera calibration include stereo imaging, depth estimation, multi-camera image fusion, and special geometry measurements.
Current methods for 3D reconstruction involve using a single camera. However, the result of single camera based methods of 3D reconstruction is that the 3D reconstruction may not be true to scale. The use of a stereo camera system may improve depth estimation. However, because precision of camera parameters is vital, the baseline of a typical stereo camera system may not be sufficient to provide accurate depth measurements for 3D reconstruction.